Prompt Claude better than 99% of people
Read time
2 min
Topics
Productivity, Remote Work, Artificial Intelligence
AI-Generated Summary
Key Takeaways
- ✓Collaborative Tone: Use friendly, clear, firm language with context instead of vague commands. Example: "Please review this text for grammatical errors and suggest corrections to make it sound more professional" outperforms "fix this grammar now" by providing direction and reducing generic responses.
- ✓Explicit Constraints: Define boundaries using action verbs, quantities, and target audiences. "Generate 10 blog post titles about remote work's impact on urban planning for city officials and real estate developers" produces focused results versus "I need blog post ideas" which yields generic output.
- ✓Draft-Plan-Act Method: Request an outline first, refine it through iteration, then execute the final version. This three-step approach saves time by enabling early course correction rather than attempting perfect one-prompt outputs that require multiple re-prompts to achieve quality results.
- ✓Power Phrases: Use specific prompting terms like "think step by step" for complex reasoning, "critique your own response" for self-correction, and "adopt the persona of an expert in [field]" to activate sophisticated AI behaviors and domain-specific vocabulary that models are trained to recognize.
What It Covers
Ten advanced prompting techniques for Claude AI based on Anthropic's official documentation, covering collaboration tone, explicit instructions, constraints, structured output, and multi-step workflows to generate higher quality, more targeted results.
Key Questions Answered
- •Collaborative Tone: Use friendly, clear, firm language with context instead of vague commands. Example: "Please review this text for grammatical errors and suggest corrections to make it sound more professional" outperforms "fix this grammar now" by providing direction and reducing generic responses.
- •Explicit Constraints: Define boundaries using action verbs, quantities, and target audiences. "Generate 10 blog post titles about remote work's impact on urban planning for city officials and real estate developers" produces focused results versus "I need blog post ideas" which yields generic output.
- •Draft-Plan-Act Method: Request an outline first, refine it through iteration, then execute the final version. This three-step approach saves time by enabling early course correction rather than attempting perfect one-prompt outputs that require multiple re-prompts to achieve quality results.
- •Power Phrases: Use specific prompting terms like "think step by step" for complex reasoning, "critique your own response" for self-correction, and "adopt the persona of an expert in [field]" to activate sophisticated AI behaviors and domain-specific vocabulary that models are trained to recognize.
Notable Moment
The host reveals that adding constraints actually increases creativity rather than limiting it. A 500-word Raymond Chandler-style robot detective story on Mars with forbidden words produces better output than simply asking for a detective story about the future.
Episode Transcript
How can you get more out of Claude Code and Claude Opus 4.5? Well, I've got good news from you. Anthropic has actually, over the last twelve months, have been posting in their in their docs, blog posts, kinda teasing on x about how you can prompt these products to really get the most out of it. But the thing is, people haven't put it in a full guide. So I did the hard work to make it easy on everyone. By the end of this episode, you will learn 10 techniques for how to prompt Claude to get the most out of it. Super simple techniques anyone can learn. I'm gonna show you real examples, easy to understand, and frameworks to help you crush it with cloud code and op Opus 4.5. Let's get right into it. So the first tip is I I know this is gonna this is gonna upset a few people, but the tone of collaboration is really important. You're gonna want a friendly and clear and firm tone because that yields better results and more direct results. So what what's an example? A vague request might be something like, fix this grammar and this now. You know? But the problem with that is, you know, oh, it leads to overly cautious, pre canned, or basically just less helpful responses as the model tries to deescalate. Politeness can sometimes result in chatty, less direct answers. Now, if you do, you know, an architected brief, and this is what the folks at Anthropic suggest you do, do something like, please review the following text for grammatical errors and suggest corrections. My goal is to make it sound more professional and confident. This is direct. This is respectful, and it provides context, which is what anthropic needs in order to get you the result, you know, that you want. So really important. I know some of us are just kind of mean to our LMS. I've been there, you know, but treat it like a teammate. Right? You would never wanna be mean to a teammate, especially if you wanna get them to produce. So, rule rule one of 10, is the tone of collaboration. Rule two of 10 is the principle of explicit explicit explicitness. So state your request as a clear action oriented command with all the necessary details. So, and I used to do this actually. I would, I would do like a vague request. Like I need a bunch of blog post ideas, but the problem is it's passive. It's not specific. And then you just get this generic AI slot architected brief. What's the difference? Okay. Generate 10 blog post titles about the impact of remote work on urban planning. The title should be engaging for an audience of city officials and real estate developers. This prompt uses an action verb, generate. You're gonna, you're gonna wanna, you know, use action verbs a lot. It specifies the quantity, 10, and target audience. …
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